Ruairi's background is in human biology. His PhD (awarded in 2021 with no corrections) centred on the application, development or evaluation of algorithms to process billions of minutes of accelerometer and physiological sensor data collected in a European epidemiological research study.
The primary objective of the PhD was to quantify metabolic rate in free-living humans. These metabolic rate estimates were used to refine mathematical models of metabolism to objectively estimate caloric intake over months and years in large cohorts.
Throughout his PhD, Ruairi was employed as a data science consultant and held numerous teaching roles, primarily in statistical and research skills. He developed a ‘statistical methods with R’ course for PhD researchers and staff.
Ruairi was subsequently employed as a postdoctoral research fellow where he designed and led an unsupervised clustering analysis of foods (~50,000) available to UK consumers.
- Classical statistics (Parametric/Non-parametric)
- Simulation and Imputation
- Mixed models
- Supervised and unsupervised machine learning
- Behavioural/Health data
- Biological signals/Wearables
- Time Series